Impact of machine and deep learning techniques on diseases classification and prediction: a systematic review

Abstract

Over the past few years, various researchers have applied machine and deep learning (DL) techniques to predict several diseases, including cancer, heart disease, Parkinson's disease, diabetes, asthma, brain tumors, obesity, skin conditions, COVID-19, Alzheimer's disease, pneumonia, and crop diseases.According to the World Health Organization (WHO) statistics, heart or cardiovascular diseases are responsible for more deaths worldwide than any other disease, accounting for 31% of all deaths. In the United States (US), this disease is the cause of one in every four deaths, with one person dying from it every 36 seconds [13]. In India, the number of deaths due to heart diseases reached approximately 4.8 million in 2020, a significant increase from the 2.26 million recorded in 1990. Recent projections indicate that India is on track to become the leader in the incidence of heart diseases [13]. *Author for correspondenceIt's worth noting that advancements in machine and DL techniques have played a crucial role in early detection, risk assessment, and treatment planning for various diseases, including heart disease.Presently, one death out of five in India is due to this disease and in upcoming years, this ratio is expected to reach up to every third death, majority will belong to the younger age groups [1]. Due to expensive diagnosis, about 75% of deaths occur in low-and middle-income countries. According to National Center for Biotechnology Information (NCBI), in every 10 years, mortality rates due to cardiovascular diseases increased about 60% in the US [2]. Deathsrelated to this disease is higher in developing countries as comparison to developed countries [3]. Obesity or overweight are the abnormal or excessive fat accumulation that presents a risk to health. Childhood and teenage obesity are one of the most serious health problems over the globe. It has spread to every country and is now a worldwide crisis in public health. All around the world, childhood and